首页> 外文会议>Proceedings of 2016 4th International Conference on Control Engineering amp; Information Technology >Face recognition using Regularized Linear Discriminant Analysis under occlusions and illumination variations
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Face recognition using Regularized Linear Discriminant Analysis under occlusions and illumination variations

机译:在遮挡和照明变化下使用正则化线性判别分析进行人脸识别

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摘要

In recent years face recognition has received substantial attention from researchers in biometrics, pattern recognition, and computer vision communities. At least two reasons account for this trend: the first is the wide range of commercial and law enforcement applications, and the second is the availability of feasible technologies in recent years of research. Many existing methods in face recognition area perform well under certain conditions, but still facing challenging with illumination changes and occlusions. This paper attempts to deal with the above challenges by combining robust illumination normalization techniques with powerful feature extraction method.
机译:近年来,人脸识别已受到生物识别,模式识别和计算机视觉社区研究人员的广泛关注。造成这一趋势的原因至少有两个:第一个是商业和执法应用的广泛范围,第二个是近年来研究中可行技术的可用性。人脸识别领域中的许多现有方法在某些条件下都能很好地发挥作用,但仍然面临光照变化和遮挡的挑战。本文试图通过结合鲁棒的照明归一化技术和强大的特征提取方法来应对上述挑战。

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